Multi‐feature fusion and memory‐based mobile robot target tracking system  

作　　者：Hanqing Sun Shijie Zhang Qingle Quan 

机构地区：[1]College of Information Engineering,Henan University of Animal Husbandry and Economy,Zhengzhou,Henan,China [2]College of Information Technology and Computer Science,University of the Cordilleras,Baguio,Philippines [3]College of Electrical Engineering,Henan University of Technology,Zhengzhou,Henan,China

出　　处：《IET Cyber-Systems and Robotics》2024年第3期62-73,共12页智能系统与机器人（英文）

基　　金：Key Discipline Project of Smart Animal Husbandry,Grant/Award Number:XJXK202201;Henan Province Science and Technology Research Projects,Grant/Award Number:232102210101。

摘　　要：In crowded settings,mobile robots face challenges like target disappearance and occlusion,impacting tracking performance.Despite existing optimisations,tracking in complex environments remains insufficient.To address this issue,the authors propose a tailored visual navigation tracking system for crowded scenes.For target disappearance,an autonomous navigation strategy based on target coordinates,utilising a path memory bank for intelligent search and re‐tracking is introduced.This significantly enhances tracking success.To handle target occlusion,the system relies on appearance features extracted by a target detection network and a feature memory bank for enhanced sensitivity.Servo control technology ensures robust target tracking by fully utilising appearance information and motion characteristics,even in occluded scenarios.Comprehensive testing on the OTB100 dataset validates the system's effectiveness in addressing target tracking challenges in diverse crowded environments,affirming algorithm robustness.

关 键 词：autonomous navigation Kalman filtering memory bank mobile robots proportional‐integral‐derivative 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]